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DANIEL GORELICK

Developer | Technologist | Engineer

Learning Neo4j Database

Motivation to use Neo4j

Here’s the thing. I need a database that works efficiently with graphs. Two people said neo4j is good, so I’m doing it!

Moving on…

Installation:

I simply did brew install neo4j then neo4j start and finally went to the http://localhost:7474/ for the build-in GUI. So far so good. It is great that this is all built in, and that there’s also a tutorial.

Useful snippets:

CREATE (ee:Person { name: "Emil", from: "Sweden", klout: 99 })

- CREATE clause to create data
- () parenthesis to indicate a node
- ee:Person a variable 'ee' and label 'Person' for the new node
- {} brackets to add properties to the node

MATCH (ee:Person) WHERE ee.name = "Emil" RETURN ee;

- MATCH clause to specify a pattern of nodes and relationships
- (ee:Person) a single node pattern with label 'Person' which will assign matches to the variable 'ee'
- WHERE clause to constrain the results
- ee.name = "Emil" compares name property to the value "Emil"
- RETURN clause used to request particular results

Creating the database

MATCH (ee:Person) WHERE ee.name = "Emil"
CREATE (js:Person { name: "Johan", from: "Sweden", learn: "surfing" }),
(ir:Person { name: "Ian", from: "England", title: "author" }),
(rvb:Person { name: "Rik", from: "Belgium", pet: "Orval" }),
(ally:Person { name: "Allison", from: "California", hobby: "surfing" }),
(ee)-[:KNOWS {since: 2001}]->(js),(ee)-[:KNOWS {rating: 5}]->(ir),
(js)-[:KNOWS]->(ir),(js)-[:KNOWS]->(rvb),
(ir)-[:KNOWS]->(js),(ir)-[:KNOWS]->(ally),
(rvb)-[:KNOWS]->(ally)

Graph created by data inserted from a Neo4j example

Graph created by data inserted from a Neo4j example

Example Queries

View everything in database

MATCH (n) RETURN n

Returns all people related to “Cloud Atlas”

MATCH (people:Person)-[relatedTo]-(:Movie {title: "Cloud Atlas"}) RETURN people.name, Type(relatedTo), relatedTo

Deleting everything in database:

MATCH (a:Person),(m:Movie) OPTIONAL MATCH (a)-[r1]-(), (m)-[r2]-() DELETE a,r1,m,r2

Useful for 6 degrees of separation

Finds all connections 4 hops away from Kevin Bacon

MATCH (bacon:Person {name:"Kevin Bacon"})-[*1..4]-(hollywood)
RETURN DISTINCT hollywood

Finds shortest path between two people

MATCH p=shortestPath(
  (bacon:Person {name:"Kevin Bacon"})-[*]-(meg:Person {name:"Meg Ryan"})
)
RETURN p

fin